code: def __init__(self, block, layers, num_classes=79077):
      super(network_29layers, self).__init__()
      self.conv1 = mfm(1, 48, 5, 1, 2)
      self.pool1 = nn.MaxPool2d(kernel_size=2, stride=2, ceil_mode=True)
      self.block1 = self._make_layer(block, layers[0], 48, 48)
      self.group1 = group(48, 96, 3, 1, 1)
      self.pool2 = nn.MaxPool2d(kernel_size=2, stride=2, ceil_mode=True)
      self.block2 = self._make_layer(block, layers[1], 96, 96)
      self.group2 = group(96, 192, 3, 1, 1)
      self.pool3 = nn.MaxPool2d(kernel_size=2, stride=2, ceil_mode=True)
      self.block3 = self._make_layer(block, layers[2], 192, 192)
      self.group3 = group(192, 128, 3, 1, 1)
      self.block4 = self._make_layer(block, layers[3], 128, 128)
      self.group4 = group(128, 128, 3, 1, 1)
      self.pool4 = nn.MaxPool2d(kernel_size=2, stride=2, ceil_mode=True)
      self.fc = mfm(7 * 7 * 128, 256, type=0)
      self.fc2 = nn.Linear(256, num_classes)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn import Parameter
label_desc: Use image node_id 1 to create a new network_29layers object from inherited base classes: nn with example: obj = network_29layers(block, layers, num_classes)